Evaluation of discovered clinical pathways using process mining and joint agent-based discrete-event simulation

Augusto, Vincent; Xie, Xiaolan; Prodel, Martin; Jouaneton, B.; Lamarsalle, Ludovic

doi:10.1109/wsc.2016.7822256

Cited by 26 publications

(15 citation statements)

References 10 publications

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“…The paper by [21] divided the applications of process mining to healthcare into two categories: medical treatment processes and organizational processes. From our 32 selected papers, there were seven studies which applied process mining in organizational processes [22]- [27], 24 studies of medical treatment processes, and one study [28] which applied process mining to both organizational and medical treatment processes. There were 20 studies based on data from hospitals including these with the hospital's respective cardiology departments or stroke units.…”

Section: Process and Data Typesmentioning

confidence: 99%

“…Of these 20 studies, there were four which used data from more than one hospital for comparative analyses [23], [29]- [31]. Three further studies used data from government-owned agencies which collect, host and analyze health data [22], [32], [33]. There were no papers using process mining to understand the disease trajectory of CVDs (also known as disease progression) although other data analytics methods have been used [34].…”

Section: Process and Data Typesmentioning

confidence: 99%

“…In term of process mining perspectives, sixteen studies only discussed the control-flow perspective [22], [25], [29], [33], [36], [37], [39], [41], [42], [44]- [50], fourteen studies discussed control-flow and performance perspectives [23], [24], [26], [30]- [32], [35], [38], [40], [51]- [55], and one study discussed all three perspectives [28]. There is one further study which discusses methods to ensure the provision high quality data for process mining [27] and this study proposed solutions to reducing errors during data-entry.…”

Section: Process Mining Perspectives Types and Toolsmentioning

confidence: 99%

“…In the limitations and future work sections of the selected papers we found limitations related to data, technique, and team. Data limitations were identified in thirteen papers [28], [23], [22], [51], [46], [53], [35], [41], [54], [29], [30], [26], [27]. The issues included the noise of the data, missing timestamp information, and data quality control.…”

Section: Limitations and Future Workmentioning

confidence: 99%

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Process Mining in Cardiology: A Literature Review

Kusuma¹,

Hall²,

Gale³

et al. 2018

IJBBB

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Process mining is a data analytics approach which has shown promising results in healthcare including the potential to improve the management of chronic diseases such as cardiovascular disease (CVD). CVD are one of the leading causes of premature death worldwide. Helping healthcare professionals develop a better understanding of how to improve CVD care pathways may result in better outcomes for patients. This paper describes the opportunities for process mining to support such improvements and provides a summary of process mining studies undertaken in the field of cardiology. The initial search found 1,597 potentially relevant papers which, after a systematic review, identified a final set of 32 relevant studies. These studies were analyzed across five themes: process and data types; research questions; techniques, perspective and tools; methodologies; limitations and suggested future work.

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Section: Process and Data Typesmentioning

confidence: 99%

Section: Process and Data Typesmentioning

confidence: 99%

Section: Process Mining Perspectives Types and Toolsmentioning

confidence: 99%

Section: Limitations and Future Workmentioning

confidence: 99%

See 2 more Smart Citations

Process Mining in Cardiology: A Literature Review

Kusuma¹,

Hall²,

Gale³

et al. 2018

IJBBB

View full text Add to dashboard Cite

show abstract

“…Process mining was applied in several research studies in health care areas Yang and Su, 2014]. For example, Augusto et al [2016] presented an automatic way to simulate and evaluate CPs. They applied their method in a severe heart failure case study.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Criteria Process Mining Optimization Tool and Its Application in a Sepsis Clinical Pathway

NEIRA¹

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Process mining applications in the healthcare domain: A comprehensive review

Guzzo

Rullo

Vocaturo

2021

WIREs Data Min & Knowl

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Process mining (PM) is a well-known research area that includes techniques, methodologies, and tools for analyzing processes in a variety of application domains. In the case of healthcare, processes are characterized by high variability in terms of activities, duration, and involved resources (e.g., physicians, nurses, administrators, machineries, etc.). Besides, the multitude of diseases that the patients housed in healthcare facilities suffer from makes medical contexts highly heterogeneous. As a result, understanding and analyzing healthcare processes are certainly not trivial tasks, and administrators and doctors look for tools and methods that can concretely support them in improving the healthcare services they are involved in. In this context, PM has been increasingly used for a wide range of applications as reported in some recent reviews. However, these reviews mainly focus on discussion on applications related to the clinical pathways, while a systematic review of all possible applications is absent. In this article, we selected 172 papers published in the last 10 years, that present applications of PM in the healthcare domain. The objective of this study is to help and guide researchers interested in the medical field to understand the main PM applications in the healthcare, but also to suggest new ways to develop promising and not yet fully investigated applications. Moreover, our study could be of interest for practitioners who are considering applications of PM, who can identify and choose PM algorithms, techniques, tools, methodologies, and approaches, toward what have been the experiences of success.

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Evaluation of discovered clinical pathways using process mining and joint agent-based discrete-event simulation

Cited by 26 publications

References 10 publications

Process Mining in Cardiology: A Literature Review

Process Mining in Cardiology: A Literature Review

A Multi-Criteria Process Mining Optimization Tool and Its Application in a Sepsis Clinical Pathway

Process mining applications in the healthcare domain: A comprehensive review

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